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Structural data were obtained by using an X-ray diffractometer with the Cu-Kα radiation and Extended X-ray absorption fine structure (EXAFS).
Based on XRD data, the crystallite size and the lattice parameters of the samples were estimated by the Scherrer and Bragg equations of the Fe(110) peak.
EXAFS data were collected from the 3C1 EXAFS beam line of the Pohang Light Source (PLS).
After that, the EXAFS data were analyzed by making use of the IFEFFIT software.
Based on these XRD data, the crystallite size and the lattice parameter (a) can be evaluated from the Scherrer and Bragg equations, Figure 3.

Table 1 shows data measured at THDi_beforeTR for each phase.
These data measured by using a reliable power meter (RPM) connected with phase wire and neutral wire.
0.297 Table 1 shows data measured at THDi_before TR at Figure 1.
These data generated by “Makmal Komputer 3” and before harmonic elimination process.
Table 2 shows data after divided by 2 between computer center_P and center_Q.

Fujian), and handled by 3086 X-Y data recorder (Sichuan Fourth Instruments).
The data were obtained from cyclic voltammograms presented in Figure2 Figure 4.
The symbols represent the experimental data, and the line is the linear fit.
A reduction peak appears at a potential of ca. -0.85 V.
Therefore, the reduction reaction of Ni(II) into metallic nickel on the Pt electrode is an irreversible process.

The IR data is consistent with the IR standard spectrum of tetrahydrofuran.
MS data for the ZrC precursor: m/z=72 (tetrahydrofuran), m/z=58(acetone), m/z=44 (carbon dioxide).
FTIR (Fig. 1) and MS (Fig. 2) data: the wavelengths of 2360cm-1 (carbon dioxide), 3014cm-1 (methane), m/z=16(methane), m/z=44(carbon dioxide).
At relatively low reaction temperature, it could not provide enough activation energy for occurrence of carbothermal reduction.
When the temperature increased from 1000°C to 1200°C, carbothermal reduction occurred, and a little of the ZrO2 was reduced to ZrC.

At the same time a weight reduction has to be achieved and the manufacturing costs have to be considered.
A weight reduction of the trackers up to 60 % was possible.
Starting basis was a market analysis of existing ultralight helicopters with regard to technical data, range of application and maximum take-off weight.
The substitution of the aluminum parts of the frame enables a weight reduction of about 45 %.
The substitution of the steel landing skid even enables a weight reduction of about 50 %.

The ANFIS network should be trained to learn about the data and its nature.
In order to determine the error between the simulated and the experimental data, the root mean square error (RMSE) is used.
In Fig. 3, the RMSE of training and checking data sets are shown for each epoch.
The terminated RMSE of training data is 0.0032.
Therefore, Fig. 4 indicates that the results derived from the ANFIS-based model agree with the experimental data well.

The reduction of the carbide grain average size was found as well (owing to nanoparticles blocking influence on re-crystallization).
A satisfactory coincidence of experimental and calculated data in the range of nanoparticles additives that do not overcome the critical concentration have been found out.
The measured data (Kic) was in a good accord with calculated from model for hard metals with mass content of nanoparticles approximately in the range 0.005-0.25.
To obtain data concerning influence of particles on properties of hard metals, each test series (beginning with preparation of initial powders) included a production of Standard basic alloys' control samples.
Adhesion wear reduction at all marks of modified hard metals was confirmed indirectly (on value reduction of surface roughness - Ra).

The system workflow is as following: Paste objective colored blocks & place pressure plate Photograph Pressure plate test Input video image BioWare Analysis Automatically recognition and track Export .txt data Get coordinates Synchronize Data Data Model 型 Compare model data Conclusion Figure 1:System Workflow Diagram Programming of data completion workflow is as following: Begin Choose video synchronized or tracking Take first frame Remove marked color Convert to grey-scale Identify removed images Noise reduction Read the next frame Save coordinate data Input video Convert to digital image Remove noise points Spot analysis Mark spot Return to coordinates Coordinate data Take first frame Subtract two grey-scale images Convert to digital image Record this frame time Input video Artificially mark synchronized signal window Convert to grey-scale
Read the next frame Check differences Synchronize data Data processing Data analysis Export report End Read pressure plate data Yes No Figure 2: Programming flowchart 3.
Convert the obtained images to binary digital images through the median filter noise reduction.
MATLAB can read data in this format, and use the great analytical mapping function to analyze data and form the chart.
Motion technology diagnostic report can be automatically formed by comparing data collected by this system with data from the template, which needs hard work.

Applying the method of finite element to research the composite damping vibration reduction effect of circular saw blade.
Extract three circular saw blades to finite element simulation analysis as relevant data plotted as shown in Figure 1 and Figure 2.
Contrast Figure 6 and Figure 7, cost the same time the C saws outer axial vibration speed is less than B outer axial vibration speed, it also explain the effect of damping vibration reduction.
The research progress of circular saw blade noise and noise reduction technology [J].
Viscoelasticity damping materials on damping noise reduction applications [J].

It first analysed the available measures regarding the reduction of ECPGDP.
The ECPGDP of Daxing District in 2010 was 0.776tce/104 CNY If there is no special declaration, the data about Daxiang District in the paper are all sources from Compilation of Economic and Social Statistics Data of Daxing District in the 11th period, Compiled by Bureau of Statistics of Daxing District, 2011, 7
The forecast value is calculated based on the time series data of permanent resident population of Daxing District form 2002~2010.
For Daxing District, because the data of energy losses are counted in the energy consumption, the measure of reducing energy loss will not be discussed here.
So, the latter two are the emphasis on the reduction of the energy intensity.